netflix_titles <- vroom::vroom('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-04-20/netflix_titles.csv') %>% 
  mutate(date_added = mdy(date_added)) %>% 
  mutate(year_added = year(date_added))

netflix_titles %>%
  head()

(
movies_country_year <- netflix_titles %>% 
  select(country, release_year, type) %>% 
  filter(release_year == 2020, !is.na(country)) %>% 
  separate_rows(country, sep = ", ") %>% 
  count(country = fct_lump(country, 10), sort = TRUE, type) %>% 
  filter(country != "Other")
)

ggplot(movies_country_year, aes(n, reorder(country, n), label = n, fill = type)) +
  geom_col(alpha = 0.7, width = 0.7, position = "dodge2") +
  geom_text(size = 3, color = "white",  position = position_dodge(width = 0.8), hjust = -1) +
  labs(
    y = "",
    x = "",
    title = "Released titles in 2020 available in Netflix",
    subtitle = "Frequency of movies releases during 2020 (the pandemic) per country, that are available in Netflix \n(Date do not correspond to Netflix release, but to the movies theirselves)",
    caption = "Data: Kaggle \n#TidyTuesday: 2021-04-17 \nPlot: @Gaspardelanoche"
  ) +
  theme(
    plot.background = element_rect(fill = "#111111"),
    panel.grid = element_line(color = "#333333", linetype = "dotted", size = 0.2),
    panel.background = element_rect(fill = "#111111"),
    axis.text.x = element_text(color = "white"),
    axis.title = element_text(color = "white"),
    axis.text.y = element_text(color = "white"),
    axis.line = element_line(color = "#333333"),
    axis.ticks = element_line(color = "gray30"),
    plot.title = element_text(color = "red", size = 20),
    plot.subtitle = element_text(color = "white", size = 13),
    plot.caption = element_text(color = "white", size = 11),
    legend.text = element_text(color = "white"),
    legend.background = element_rect(fill = "#111111"),
    legend.position = "bottom",
    legend.title = element_blank()
  ) +
  scale_fill_manual(values = c("#FAF5FF","#FF0000"))

(
movies_country_years <- netflix_titles %>% 
  select(country, release_year, type) %>% 
  filter(!is.na(country), !is.na(release_year)) %>% 
  separate_rows(country, sep = ", ") %>% 
  count(country = fct_lump(country,10), sort = TRUE, release_year) %>% 
  pivot_wider(names_from = release_year, values_from = n) %>% 
  mutate(across(everything(), ~replace_na(., 0))) %>% 
  pivot_longer(!c(country,), names_to = "release_year",  values_to = "n") %>% 
  filter(country != "Other") %>% 
  group_by(country) %>% 
  arrange(release_year) %>%
  summarize(release_year, cumsum = cumsum(n), n, .groups = "drop") %>%
  # ungroup() %>% 
  group_by(release_year) %>% 
  mutate(ordering = rank(cumsum, ties.method = "first"), release_year = as.integer(release_year), cumsum_lab = as.character(cumsum))
)

movies_country_years_animated <- ggplot(movies_country_years, aes(ordering, group = country)) +
  geom_tile(aes(y = cumsum/2, height = cumsum, width = 0.9), alpha = 0.5, fill = "red") +
  geom_text(aes(y = 0, label = country), hjust = 1.1, color = "white") +
  geom_text(aes(y = cumsum, label = cumsum_lab), size = 3, color = "white", hjust = -0.5) +
  coord_flip(clip = "off", expand = FALSE) +  
  labs(
    y = "",
    x = "",
    title = "Released titles in {frame_time} available in Netflix",
    subtitle = "Frequency of movies released in {frame_time} country, that are available in Netflix \n(Date do not correspond to Netflix release, but to the movies theirselves)",
    caption = "Data: Kaggle \n#TidyTuesday: 2021-04-17 \nPlot: @Gaspardelanoche"
  ) +
  theme(
    plot.background = element_rect(fill = "#111111"),
    panel.grid = element_line(color = "#333333", linetype = "dotted", size = 0.2),
    panel.background = element_rect(fill = "#111111"),
    axis.text.x = element_text(color = "white"),
    axis.title = element_text(color = "white"),
    axis.text.y = element_blank(),
    axis.line = element_line(color = "#333333"),
    axis.ticks = element_line(color = "gray30"),
    plot.title = element_text(color = "red", size = 20),
    plot.subtitle = element_text(color = "white", size = 13),
    plot.caption = element_text(color = "white", size = 11),
    legend.text = element_text(color = "white"),
    legend.title = element_blank(),
    plot.margin = margin(4, 4, 4, 4, "cm")
  )  +
  transition_time(release_year) +
  ease_aes('bounce-in-out')

animate(movies_country_years_animated, nframes = 500, fps = 10, width = 800, height = 800, end_pause = 25)